Oct 25, 2022 · Following the method of moments, we tackle an incomplete tensor decomposition problem to learn the mixing weights and componentwise means. Then ...

In terms of computational advances, Sherman and Kolda [44] proposed implicit tensor decomposition to avoid expensive tensor formation when applying MoM.

Dec 7, 2023 · Following the method of moments, we tackle an incomplete tensor decomposition problem to learn the mixing weights and componentwise means. Then ...

Following the method of moments, we tackle a coupled system of low-rank tensor decomposition problems. The steep costs associated with high-dimensional tensors ...

An alternating least squares type numerical optimization scheme to estimate conditionally-independent mixture models in $\mathbb{R}^n$ without ...

In this chapter we use an Empirical Bayes approach to estimate the hyperparameters for each level of the wavelet decomposition, bypassing the usual ... [Show ...

Jan 4, 2023 · ▷ It is useful to build algorithms to decompose sample moments which do not explicitly form the high-dimensional tensors. Page 25. References. ▷ ...

This is an implementation of the algorithms in Moment Estimation for Nonparametric Mixture Models through Implicit Tensor Decomposition by Yifan Zhang and Joe ...

Jan 11, 2024 · Yifan Zhang, Joe Kileel, “Moment estimation for nonparametric mixture models through implicit tensor decomposition”, SIAM Journal on Mathematics.

In this work, we develop theory and numerical methods for \emph{implicit computations} with moment tensors of GMMs, reducing the computational and storage costs ...